Wednesday, April 8, 2026

ProPublica Workers Strike to Prevent AI Layoffs

Some stories, such as workers striking to gain automation-caused protections, are quite evergreen. 


Although workers at ProPublica are striking over a range of issues from layoffs, artificial intelligence to wages, the historical record suggests automation is very hard to resist. 


Protections against technological displacement (explicit contract language barring AI-generated layoffs or replacement of bargaining-unit work) have not shielded newsrooms from economic displacement. 


These clauses typically prohibit layoffs solely or directly caused by automation but explicitly allow (or do not block) reductions for “financial reasons,” revenue shortfalls, strategic pivots, or cost-cutting tied to broader business model failures (collapsing print advertising and licensing revenue, subscription challenges, digital platform shifts, and legacy media contraction).


And it is the business model changes that have caused layoffs in content-producing industries. 


Outlet / Period

Union & Tech Protection Won

Primary Business-Model / Economic Driver

Layoffs / Buyouts Outcome

Tech Protections’ Effectiveness Against Economic Cuts

Sources

CalMatters (late 2024–Mar 2025)

NewsGuild first contract (ratified ~early 2025) included AI layoff protections (similar to industry-standard bans on gen-AI-caused reductions)

Nonprofit revenue/funding pressures amid industry-wide contraction

Layoffs occurred shortly after contract victory despite the new AI and just-cause safeguards

None – economic cuts proceeded post-ratification

NewsGuild: “A hard-fought first contract victory at CalMatters, followed by layoffs”

Ziff Davis Creators Guild (Mashable, CNET, PCMag, etc.) (Jul 2024–Jul/Aug 2025)

First to win explicit language (Jul 2024): “No layoffs… as a result of generative AI” + no base-salary cuts from AI

Corporate restructuring/buyouts at multibillion-dollar parent Ziff Davis; cuts framed as efficiency measures across properties (company reported strong financials)

23 layoffs (15% of union bargaining unit) in Jul 2025 across CNET/Lifehacker/Mashable/ZDNet; additional rounds (e.g., 8 at IGN, 12% of unit) followed buyouts

Low – layoffs explicitly not tied to AI; union protested as non-journalism-related cost-cutting

NewsGuild statement on layoffs (Jul 31, 2025); The Verge (Jul 30, 2025); Game Developer (Aug 5, 2025)

Associated Press (2024–Apr 2026)

News Media Guild editorial-unit contract (2024) included AI layoff protections (one of the early wave of similar clauses)

25% revenue decline from newspaper licensing (4 years); strategic pivot away from print-era model toward visual journalism + new revenue (incl. AI-investing clients)

Buyouts offered to >120 U.S. journalists (Apr 2026); targeted <5% global staff reduction

None – buyouts framed purely as economic pivot; union noted company “flirting with artificial intelligence” while cutting human staff

AP News (Apr 2026)

Industry-wide (2025–early 2026)

58+ NewsGuild units with AI protections (no-AI-layoffs clauses, notice/bargaining, “tool only” language)

Structural collapse: ad revenue migration to platforms, subscription fatigue, legacy print decline, cost pressures

Ongoing wave of hundreds of cuts (WaPo ~1/3 newsroom, CBS 6%, others at Politico/Vox/Nexstar/etc.); many via buyouts or economic layoffs

Limited overall – protections block AI-specific displacement but not revenue-driven restructuring

Press Gazette 2026 layoff tracker; Nieman Lab (Mar 2026)

Journalism unions (primarily the NewsGuild-CWA, formerly Newspaper Guild, and historically the International Typographical Union/ITU for production roles) have had limited long-term success in preventing layoffs directly caused by automation


They have occasionally delayed technological adoption, secured transitional protections (lifetime job guarantees, enhanced severance, retraining, or "no-layoff" clauses for incumbents), or won contract language prohibiting automation/AI from reducing bargaining-unit work. 


But major workforce reductions have occurred, anyway. 


Period/Event

Union/Outlet

Automation Issue

Union Actions, Demands

Outcome

Effectiveness in Preventing Layoffs

1962–1963

ITU Local 6 / 7 NYC dailies (e.g., NYT)

Computerized typesetting (early automation)

114-day strike to restrict new tech, protect composing-room jobs, and gain jurisdiction

Strike ended with limited concessions; 4 papers eventually closed; long-term automation advanced

Low – Delayed some changes but accelerated industry decline and job losses in production.Vanity Fair (2012); History of Information

1970s–1980s (Cold Type era)

ITU (typesetters) / Various newspapers (e.g., Columbus Dispatch)

Photocomposition, computerized pagination replacing hot-metal linotype

Negotiated lifetime job guarantees, no-layoff clauses for incumbents, attrition-based reductions

Protections for existing workers; massive reductions via attrition (e.g., one union local from ~500 to ~50 printers)

Moderate short-term (no immediate mass firings for protected workers) but low overall – composing rooms largely eliminateds.

Type Investigations (2015)

2023–2025 (AI contract wave)

NewsGuild units (e.g., The New Republic, POLITICO/PEN Guild, NYT)

Generative AI for content creation, summarization, etc.

Contract language: ban AI layoffs/replacement of unit work; AI as "tool only"; 60–90 day notice + bargaining; oversight

Multiple contracts ratified with explicit protections; POLITICO won landmark arbitration enforcing notice/bargaining

High in contract terms (prohibits AI-driven layoffs in covered units); enforcement via arbitration tested successfully. NewsGuild (2025); New Republic ratification; POLITICO arbitration

2024–2026

News Media Guild / Associated Press

AI tools + pivot away from print (buyouts)

Demands for AI bargaining, limits on AI replacing editorial work, protections against buyouts tied to automation

Buyouts offered to ~120+ staff; union alleges company ignored AI bargaining request

Low/ongoing – Buyouts proceeded; no full prevention of reductions

March 2026 (ongoing)

ProPublica Guild (NewsGuild) / ProPublica

AI adoption potentially causing layoffs

Strike authorization (92% yes) demanding ban on AI-related layoffs, just cause, seniority in layoffs

Strike authorized but not yet executed (bargaining continued post-vote); management offered severance instead of ban

TBD – First major newsroom action explicitly over AI protections; tests strength of demands. Nieman Lab (Mar 2026); NewsGuild


The bottom line is that although a key contract demand is that there be no layoffs because of automation, such clauses do not prevent layoffs for economic reasons. And economic pressure is typically what drives the automation. 


Tuesday, April 7, 2026

Far Side of the Moon from Artemis II

 From Artemis II: earth and the far side of the moon

source: NASA

Monday, April 6, 2026

Gemma 4 is Designed to Run on Edge Devices Such as Smartphones, Using Apache 2.0 License

Gemma 4, Google’s latest open source artificial intelligence model, is probably important for several reasons. For starters, it uses an Apache 2.0 license model, which means that developers can take Gemma 4, fine-tune it, ship it in a product, charge money for it, and Google has no claim over what you built.

You might argue that closed models are irrelevant for most independent developers and small companies, as they are expensive at scale, opaque, and make developers permanently dependent on another company’s pricing decisions.


Gemma changes the payback model. You host it, control the data and tune it to your use case. Developers pay for compute, not per-token fees.


Also, the models are engineered from the ground up for maximum compute and memory efficiency, to preserve RAM and battery life. 


“These multimodal models run completely offline with near-zero latency across edge devices like phones, Raspberry Pi, and NVIDIA Jetson Orin Nano,” Google notes, with the more-complex models running on a single graphics processor unit.


But Gemma 4 is optimized for on-device and low-resource environments, including mobile. That enables:


Since Gemma 4 reduces inference and application programming interface costs, which are run locally, startups and independent developers can build AI products with much lower marginal cost, expanding the range of viable business models, especially for specialized use cases.  


Of course, as often is the case for open source, there are advantages for the sponsor. 


Historically, Google uses open tools to drive developer adoption and ecosystem lock-in, and Gemma 4 arguably fits that pattern:

  • Free/open models attract developers

  • Developers build apps

  • Apps are hopefully hosted on Google Cloud. 


Ideally, from Google’s point of view, the idea is to remain relevant no matter what happens with the cloud computing inference business


Old model

Emerging model

Centralized cloud inference

Distributed + edge inference

Pay-per-API-call

Local + hybrid

Vendor-controlled

Developer-controlled


Also, Gemma 4 diversifies Google’s model approach. Where Gemma targets the segment of the market requiring  open, lightweight, customizable solutions, Gemini focuses on the segment where proprietary, frontier, premium models are valued. 


So Gemma should appeal to users focused on experimentation, edge computing and cost-sensitive use cases. Gemini remains focused on high-end reasoning and enterprise-grade reliability.


Sunday, April 5, 2026

First Movers Can Attain Sustainable Advantage, But It is Hard to Accomplish

Some might argue that firms deploying artificial intelligence early will gain a sustainable advantage over others in their industry and category. I tend to doubt that. 


The issue is that some firms might have other advantages. They might be better managed in general; more adaptable; more agile. The point is that they might do most things better than competitors, including using new technology. 


The management literature generally supports the idea that sustainable advantage is quite rare, and where it happens, might be explained by other advantages than the early deployment of a new technology. 


In short, being first to deploy a significant technology is, by itself, not a reliable source of sustained competitive advantage.


Lieberman and Montgomery's First-Mover Advantages are foundational studies.


The time for competitors to enter a new product market has shrunk dramatically from 33 years early in the 20th century to 3.4 years later in the century and continues to shrink. So first-mover advantage exists, but most likely will be a fleeting advantage. 


And early technology adoption by itself is not a determinant of sustained competitive advantage. Instead, it usually indicates there are other mechanisms at work. 


Early movers only create enduring benefits when their timing advantage is simultaneously mobilized with network effects, aligned with competence-enhancing trajectories, sustained partner rents across the value network and continuous absorption of external knowledge, for example. 


Almost by definition, new technologies that prove to have value will be accessible to all, over time (technology that enterprises can afford eventually are adapted for mid-market and finally small businesses or individuals. 


For competitive advantage to be sustained over time, barriers to imitation must exist. 


“The problem for Kmart and other wannabe Wal-Marts is what Lippman and Rumelt

refer to as causal ambiguity,” say the authors of The Analysis of Competitive Advantage.  


“The more multidimensional a firm’s competitive advantages might be, and the more each dimension of competitive advantage is based on complex bundles of organizational capabilities rather than individual resources, the more difficult it is for a competitor to diagnose the determinants of success,” they state. 


“The outcome of causal ambiguity is uncertain imitability: where there is ambiguity associated with

the causes of a competitor’s success, any attempt to imitate that strategy is subject to

uncertain success,” they add.


In other words, sustainable advantage might happen when competitors are uncertain about how a particular innovation adds value, in a mix of value drivers. 


On the other hand, that is probably the outlier. 


Contemporary research from Harvard Business School indicates that first-mover companies achieve sustainable competitive advantage in only 37 percent of new market categories, while fast followers demonstrate superior long-term profitability in 42 percent  of markets studied.


Being a fast follower often results in long-term advantage, some studies have found. 


Still, some studies suggest when sustainable advantage might be generated. 


Network effects are a classic example. When a product or platform becomes more valuable as more people use it, early movers can lock in users before alternatives exist. 


Proprietary technology plus early entry can offer sustainable advantages, as can switching costs and ecosystem lock-in.


Still, first movers often do not succeed. When a new technology destroys the value of an incumbent's existing capabilities or partner relationships, early deployment can be a liability, if fast followers are agile enough. 


But the rule might well be that when new technologies are able to gain wide adoption, sustainable advantage cannot be maintained by a first mover. 


The research suggests that durable advantage comes not from deploying a technology first, but from what a firm builds on top of that deployment:


Without those, competitors do, as a general pattern, catch up, and often faster with each passing decade.

ProPublica Workers Strike to Prevent AI Layoffs

Some stories, such as workers striking to gain automation-caused protections, are quite evergreen.  Although workers at ProPublica are stri...